Shocking! While generative AI sweeps the consumer market, creating a boom in efficiency tools, AI adoption in the B2B enterprise management software sector remains remarkably slow! Even leading digital enterprises often see AI applications stuck in a “plugin” phase, merely serving as “assistant-level” functions for report generation or document summarization. Behind this lies the inherent complexity of enterprise management systems: inconsistent processes, rigid permission structures, strong organizational resistance, and stringent localization and regulatory requirements! For AI to truly integrate into enterprise workflows, it's far more than just adding a smart input box!
This is precisely the context in which the VPS chose to start from “processes” and undertake a “bottom-up reconstruction.” We didn't shy away from this tough challenge. Instead, we asked: What if, instead of making AI adapt to existing systems, we rebuilt a system for AI? Would that truly enable intelligent management?
A Paradigm Shift from AI Features to an AI Operating System
Traditional enterprise management software often treats AI as a “feature plugin,” like patching an old computer. But the VPS takes a fundamentally different approach! We're unveiling a “bottom-up reconstruction” product suite: an Intelligent Agent Matrix and an Agent 2.0 Platform.
- Intelligent Agent Matrix: We transform AI into “task-oriented employees” within the enterprise. We've developed dedicated intelligent agents for high-frequency scenarios like financial analysis, data querying, recruitment, travel management, and knowledge management. These aren't just simple AI feature encapsulations; they are “digital employees” with a complete “perceive → understand → decide → execute” loop, capable of cross-system information retrieval, context-aware responses, and even collaboration with other agents!
- Agent 2.0 Platform: If intelligent agents are the “application layer” solving specific problems, then our Agent Platform is the “operating system layer” for enterprise AI! It provides templated task flows, system integration components, multi-model collaboration mechanisms, enterprise-grade RAG with permission management, and multi-device deployment capabilities. Here, enterprises no longer passively await AI product updates; they can generate, combine, govern, and evolve intelligent agents based on their business needs. This is more than just a “development toolkit”; it's a platform that empowers enterprises to build and manage their own AI systems and AI employees!
AI Implementation Shifts from Model-Centric to Management System-Centric
Many companies discussing AI implementation still focus on “which large model is stronger?” But the VPS believes that the real problems enterprises need to solve are not “insufficient AI capabilities,” but “overly complex business processes, disconnected data, and organizational resistance to change”! We've bypassed the “algorithm race” and chosen to return to processes, interfaces, and operational details – our goal is to create AI that is better suited for the internal operational structure of enterprises, not just stronger AI. This represents a fundamental shift: an AI design philosophy moving from “model-centric” to “management system-centric.” With over three decades of deep experience in enterprise management, we possess profound scenario understanding, inherent data connectivity, and mastery over multi-model combinations, allowing us to truly penetrate the “structural depths” of enterprise management.
The Governability of Enterprise AI is More Crucial Than Its Generative Capability
In enterprise scenarios, whether AI can generate content is not the primary concern. What's more critical is whether it can be authorized to execute, audited for traceability, granted layered permissions, and isolated for data security! The VPS Agent Platform is called “enterprise-grade” precisely because it possesses the “sense of responsibility boundaries” that enterprises require. Who triggers? Who approves? Who has access permissions? How are processes logged? These factors determine whether AI can be trusted and truly become central to enterprise operations. Our “AIGO Methodology” (Assessment & Architecture, Implementation, Governance, Operation & Optimization) is an AI implementation framework designed for “complex organizations,” transforming AI deployment from “delivering features” into “building capabilities.”
Conclusion
We stand at the threshold of a new era. B2B AI won't go viral overnight like C2C AI; its evolution is more like a structural reshaping in deep waters – slow, restrained, yet step by step. What the VPS presents is a signal that an enterprise-grade AI architecture is taking shape. It transforms AI from an external “auxiliary tool” into the “initiator, executor, and feedback provider” of business processes, fundamentally redefining how enterprises operate.